Discontinuity set extraction from 3D point clouds obtained by UAV Photogrammetry in a rockfall site

Yakar, Murat; Ulvi̇, Ali̇; Yi̇ği̇t, Abdurahman Yasi̇n; Alptekin, Aydın

doi:10.1080/00396265.2022.2119747

Cited by 28 publications

(12 citation statements)

References 61 publications

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“…Photogrammetry is a technique that derives the required information by creating a 3D model from 2D images. Common points are matched from a series of overlapping 2D images to create the 3D model through Structure-from-Motion (SfM) technology [ 49 , 50 , 51 ]. The photogrammetry technique has been applied in many fields such as surveying, civil engineering, urban planning, gas detection, fire monitoring, archeology, mining, industry, urban management, agriculture, and forest management [ 49 , 51 , 52 ].…”

Section: Review Of Literaturementioning

confidence: 99%

UAV Photogrammetry for Estimating Stand Parameters of an Old Japanese Larch Plantation Using Different Filtering Methods at Two Flight Altitudes

Karthigesu,

Owari,

Tsuyuki

et al. 2023

Sensors

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Old plantations are iconic sites, and estimating stand parameters is crucial for valuation and management. This study aimed to estimate stand parameters of a 115-year-old Japanese larch (Larix kaempferi (Lamb.) Carrière) plantation at the University of Tokyo Hokkaido Forest (UTHF) in central Hokkaido, northern Japan, using unmanned aerial vehicle (UAV) photogrammetry. High-resolution RGB imagery was collected using a DJI Matrice 300 real-time kinematic (RTK) at altitudes of 80 and 120 m. Structure from motion (SfM) technology was applied to generate 3D point clouds and orthomosaics. We used different filtering methods, search radii, and window sizes for individual tree detection (ITD), and tree height (TH) and crown area (CA) were estimated from a canopy height model (CHM). Additionally, a freely available shiny R package (SRP) and manually digitalized CA were used. A multiple linear regression (MLR) model was used to estimate the diameter at breast height (DBH), stem volume (V), and carbon stock (CST). Higher accuracy was obtained for ITD (F-score: 0.8–0.87) and TH (R2: 0.76–0.77; RMSE: 1.45–1.55 m) than for other stand parameters. Overall, the flying altitude of the UAV and selected filtering methods influenced the success of stand parameter estimation in old-aged plantations, with the UAV at 80 m generating more accurate results for ITD, CA, and DBH, while the UAV at 120 m produced higher accuracy for TH, V, and CST with Gaussian and mean filtering.

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Section: Review Of Literaturementioning

confidence: 99%

UAV Photogrammetry for Estimating Stand Parameters of an Old Japanese Larch Plantation Using Different Filtering Methods at Two Flight Altitudes

Karthigesu,

Owari,

Tsuyuki

et al. 2023

Sensors

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“…Camera-based monitoring techniques have recently been used to monitor and track fallen rocks in real time. More recently, the development of photogrammetric monitoring systems for rock-fall monitoring purposes has received increased attention in the scientific literature [8][9][10][11][12]. A test version of an artificial intelligence camera was used to track and monitor falling rocks in real-time [13].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning- and IoT-Based Framework for Rock-Fall Early Warning

Abaker,

Dafaalla,

Eisa

et al. 2023

Applied Sciences

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In recent years, several strategies have been introduced to enhance early warning systems and lower the risk of rock-falls. In this regard, this paper introduces a deep learning- and IoT-based framework for rock-fall early warning, devoted to reducing rock-fall risk with high accuracy. In this framework, the prediction accuracy was augmented by eliminating the uncertainties and confusion plaguing the prediction model. In order to achieve augmented prediction accuracy, this framework fused prediction model-based deep learning with a detection model-based Internet of Things. This study utilized parameters, namely, overall prediction performance measures based on a confusion matrix, to assess the performance of the framework in addition to its ability to reduce the risk. The result indicates an increase in prediction model accuracy from 86% to 98.8%. In addition, the framework reduced the risk probability from 1.51 × 10−3 to 8.57 × 10−9. Our findings demonstrate the high prediction accuracy of the framework, which also offers a reliable decision-making mechanism for providing early warning and reducing the potential hazards of rock falls.

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“…Unmanned aerial vehicles are frequently used in different areas such as agriculture, mining, construction, natural disaster monitoring, meteorology, archeology, imdustry especially cartography [4][5][6][7][8][9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Exploring structural deterioration at historical buildings with UAV photogrammetry

DÖRTBUDAK,

AKÇA,

POLAT

2023

Cultural Heritage and Science

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The preservation and transmission of cultural heritage to future generations are crucial in today's rapidly advancing world. This study focuses on the application of Unmanned Aerial Vehicle (UAV) technology and photogrammetric techniques in the modeling and documentation of Germus Church, a significant cultural heritage site. The research aims to create a high-fidelity 3D model of the church, capturing its architectural intricacies and deformations caused by time and damage. The fieldwork involved capturing aerial photographs using a DJI Mavic 2 Pro UAV system, followed by image processing with Structure-from-Motion (SfM) software. The generated 3D model revealed extensive deformations, including cracks, collapses, and loss of religious figures and decorations. The findings emphasize the importance of preserving and restoring Germus Church for tourism promotion. The study showcases the effectiveness of UAV technology in documenting cultural heritage and highlights its potential for future applications. The 3D model serves as a valuable resource for researchers, historians, and the public, fostering a deeper understanding and appreciation of our rich cultural heritage.

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Discontinuity set extraction from 3D point clouds obtained by UAV Photogrammetry in a rockfall site

Cited by 28 publications

References 61 publications

UAV Photogrammetry for Estimating Stand Parameters of an Old Japanese Larch Plantation Using Different Filtering Methods at Two Flight Altitudes

UAV Photogrammetry for Estimating Stand Parameters of an Old Japanese Larch Plantation Using Different Filtering Methods at Two Flight Altitudes

Deep Learning- and IoT-Based Framework for Rock-Fall Early Warning

Exploring structural deterioration at historical buildings with UAV photogrammetry

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